Work

An Interaction Based Composable Architecture for Building Scalable Models of Large Social, Biological, Information and Technical Systems.

Year: 2008

Type: article

Abstract: This article describes our ongoing efforts to develop a global modeling, information & decision support cyberinfrastructure (CI) that will provide scientists and engineers novel ways to study large complex socio-technical systems. It consists of the following components: High-resolution scalable models of complex socio-technical systems Service-oriented architecture and delivery mechanism for facilitating the use of these models by domain experts Distributed coordinating architecture for information fusion, model execution and data processing Scalable data management architecture and system to support model execution and analytics Scalable methods for visual and data analytics to support analysts To guide the initial development of our tools, we are concentrating on agent-based models of inter-dependent societal infrastructures, spanning large urban regions. Examples of such systems include: regional transportation systems; regional electric power markets and grids; the Internet; ad-hoc telecommunication, communication and computing systems; and public health services. Such systems can be viewed as organizations of organizations. Indeed, functioning societal infrastructure systems consist of several interacting public and private organizations working in concert to provide the necessary services to individuals and society. Issues related to privacy of individuals, confidentiality of data, data integrity and security all arise while developing microscopic models for such systems. See [1] [2] [3] for additional discussion (also see Figure 1). Figure 1 Schematic of societal infrastructure systems (adapted from [2]). The need to represent functioning population centers during complex incidents such as natural disasters and human initiated events poses a very difficult scientific and technical challenge that calls for new state-of-the-art technology. The system must be able to handle complex co-evolving networks with over 300 million agents (individuals), each with individual itineraries and movements, millions of activity locations, thousands of activity types, and hundreds of communities, each with local interdependent critical infrastructures. The system must be able to focus attention on demand and must support the needs of decision makers at various levels. The system must also support related functions such as policy analysis, planning, course-of-action analysis, incident management, and training in a variety of domains (e.g., urban evacuation management, epidemiological event management, bio-monitoring, population risk exposure estimation, logistical planning and management of isolated populations, site evacuations, interdependent infrastructure failures). Constructing large socio-technical simulations is challenging and novel, since, unlike physical systems, socio-technical systems are affected not only by physical laws but also by human behavior, regulatory agencies, courts, government agencies and private enterprises. The urban transportation system is a canonical example of such interaction; traffic rules in distant parts of the city can have an important bearing on the traffic congestion in downtown, and seemingly “reasonable” strategies such as adding a new road somewhere might worsen the traffic. The complicated inter-dependencies within and among various socio-technical systems, and the need to develop new tools, are highlighted by the failure of the electric grid in the northeastern U.S in 2003. The massive power outage left people in the dark along a 3,700 mile stretch through portions of Michigan, Ohio, Pennsylvania, New Jersey, New York, Connecticut, Vermont and Canada. Failure of the grid led to cascading effects that slowed down Internet traffic, closed down financial institutions and disrupted the transportation; the New York subway system came to a halt, stranding more than 400,000 passengers in tunnels [4]. The CI we are building was motivated by the considerations to understand the complex inter-dependencies between infrastructures and the society as described above. Over the past 15 years and in conjunction with our collaborators, we have established a program for modeling, simulation and associated decision support tools for understanding large socio-technical systems. The extremely detailed, multi-scale computer simulations allow users to interact among themselves as well as interact with the environment and the networked infrastructure. The simulations are based on our theoretical program in discrete dynamical systems, complex networks, AI and design and analysis of algorithms (see [2] [5] [6] [7] [8]and the references therein). Until 2003, much of our efforts were concentrated on building computational models of individual infrastructures, see [2]. Over the last 7-10 years, significant advances have been made in developing computational techniques and tools that have the potential of transforming how these models are delivered to and used by the end users [9] [10] [11]. This includes, web services, grid computing and methods to process large amounts of data. With the goal of harnessing this technology, since 2005, we have expanded the scope of our effort. In addition to building scalable models, we have also begun the development of an integrated CI for studying such inter-dependent, socio-technical systems. It consists of mechanisms to deliver the access to these models to end users over the web, development of a data management environment to support the analysis and data, and a visual analytics environment to support decision-making and consequence analysis (see [2] [6]). The CI will provide social scientists unprecedented Internet-based access to data and models pertaining to large social organizations. In addition, the associated modeling tools will generate new kinds of synthetic data sets that cannot be created in any other way (e.g., direct measurement). The data generated by these methods will protect the privacy of individuals as well as the confidentiality of data obtained from proprietary datasets. This will enable social scientists to investigate entirely new research questions about functioning societal infrastructures and the individuals interacting with these systems. Everything, from the scope and precision of socio-technical analysis to the concept of collaboration and information integration, will change, as a dispersed framework that supports detailed interdependent interaction of very large numbers of complex individual entities that come into use and evolve. The tools will also allow policy makers, planners, and emergency responders unprecedented opportunities for coordination of and integration with the information for situation assessment and consequence management. This is important for planning and responding in the event of a large-scale disruption of the societal infrastructures.

Source: PubMed